Spam Filter by Using X2 Statistics and Support Vector Machines 


Vol. 17,  No. 3, pp. 249-254, Jun.  2010
10.3745/KIPSTB.2010.17.3.249


PDF
  Abstract

We propose an automatic spam filter for e-mail data using Support Vector Machines(SVM). We use a lexical form of a word and its part of speech(POS) tags as features and select features by chi square statistics. We represent each feature by TF(text frequency), TF-IDF, and binary weight for experiments. After training SVM with the selected features, SVM classifies each e-mail as spam or not. In experiment, the selected features improve the performance of our system and we acquired overall 98.9% of accuracy with TREC05-p1 spam corpus.

  Statistics
  Cite this article

[IEEE Style]

S. W. Lee, "Spam Filter by Using X2 Statistics and Support Vector Machines," The KIPS Transactions:PartB , vol. 17, no. 3, pp. 249-254, 2010. DOI: 10.3745/KIPSTB.2010.17.3.249.

[ACM Style]

Song Wook Lee. 2010. Spam Filter by Using X2 Statistics and Support Vector Machines. The KIPS Transactions:PartB , 17, 3, (2010), 249-254. DOI: 10.3745/KIPSTB.2010.17.3.249.

Forms

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)

Old Journals

Indexing

All publications of TKIPS is indexed in DOI, EBSCO, Google Scholar, Crossref, and CrossCheck.

TKIPS is also selected as the Journal for Accreditation by NRF (National Research Foundation of Korea).

Related Journals